Highlights Dual-credit policy has made electrification of traditional automakers inevitable. This study considers stochastic credit prices and time-dependent investment costs. It presents an optimal decision model with three indicators for automakers. Electrification is not optimal for medium-sized automakers at current credit price. Tightening the rules is not necessarily beneficial for facilitating electrification.

    Abstract The newly introduced dual-credit policy has made electrification inevitable for traditional automakers. This study considers stochastic credit prices and time-dependent electric vehicle (EV) investment costs to present a novel optimal decision model with three indicators: investment timing, research and development intensity, and product line allocation. This combinatorial optimization problem is solved by developing a genetic algorithm. The simulation result shows that the high profitability of EVs can accelerate electrification, while rapid credit price increases may instead d[1]elay it. Meanwhile, the Corporate Average Fuel Consumption (CFAC) credit rules outperform the New Energy Vehicle (NEV) credit rules in facilitating electrification and driving long-term cumulative EV productions. Interestingly, despite the pressure these rules bring, tightening them is not necessarily beneficial for boosting electrification. Overall, introducing credit ceiling and floor prices, or coordinating policy parameters by steadily tightening CAFC rules while appropriately moderating NEV rules, would effectively accelerate electrification and promote EV productions.


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    Title :

    Electrification decisions of traditional automakers under the dual-credit policy regime


    Contributors:
    He, Haonan (author) / Li, Shiqiang (author) / Wang, Shanyong (author) / Chen, Zhuru (author) / Zhang, Jinxi (author) / Zhao, Jie (author) / Ma, Fei (author)


    Publication date :

    2021-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






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